Resolving user expression having dependent intents

ABSTRACT

The exemplary embodiments disclose a system and method, a computer program product, and a computer system for resolving the intents of user expression. The exemplary embodiments may include receiving a user expression, receiving a first resolver having an input class and an output class based on the user expression, determining whether the first resolver can be resolved based on the user expression, and based on determining that the first resolver can be resolved based on the user expression, resolving the first resolver.

BACKGROUND

The exemplary embodiments relate generally to resolving user intents,and more particularly to resolving user intents of a user expressionhaving multiple embedded and dependent intents.

Humans often communicate with automated computers or machines, such asautomated phone call answering machines, smart speakers, smartassistants, and the like. In practice, it may be difficult for automatedcomputers or machines to adequately respond to humans or adequatelyfulfill their requests without understanding their intentions. In orderto understand human intentions, it is often necessary to understand theintents of human inputs and expression, such as a message, command,question, and the like. Moreover, often times such human expression mayinclude multiple intents, and such intents may be dependent on theresolving of other intents within the human inputs. It is thereforenecessary to resolve each of the intents of human expression toadequately understand and respond to human prompts.

SUMMARY

The exemplary embodiments disclose a system and method, a computerprogram product, and a computer system for resolving the intents of userexpression. The exemplary embodiments may include receiving a userexpression, receiving a first resolver having an input class and anoutput class based on the user expression, determining whether the firstresolver can be resolved based on the user expression, and based ondetermining that the first resolver can be resolved based on the userexpression, resolving the first resolver.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

The following detailed description, given by way of example and notintended to limit the exemplary embodiments solely thereto, will best beappreciated in conjunction with the accompanying drawings, in which:

FIG. 1 depicts an exemplary schematic diagram of an intent resolversystem 100, in accordance with the exemplary embodiments.

FIG. 2 depicts an exemplary flowchart 200 illustrating the operations ofan intent resolver 134 of the intent resolver system 100 in resolvingthe intents of one or more user expressions, in accordance with theexemplary embodiments.

FIG. 3 depicts an illustrative example of the intent resolver system 100resolving a user expression, in accordance with the exemplaryembodiments.

FIG. 4 depicts an illustrative example of a collated output based ondependency generated by the intent resolver system 100 in resolving theuser expression of FIG. 3, in accordance with the exemplary embodiments.

FIG. 5 depicts an exemplary block diagram depicting the hardwarecomponents of the intent resolver system 100 of FIG. 1, in accordancewith the exemplary embodiments.

FIG. 6 depicts a cloud computing environment, in accordance with theexemplary embodiments.

FIG. 7 depicts abstraction model layers, in accordance with theexemplary embodiments.

The drawings are not necessarily to scale. The drawings are merelyschematic representations, not intended to portray specific parametersof the exemplary embodiments. The drawings are intended to depict onlytypical exemplary embodiments. In the drawings, like numberingrepresents like elements.

DETAILED DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

Detailed embodiments of the claimed structures and methods are disclosedherein; however, it can be understood that the disclosed embodiments aremerely illustrative of the claimed structures and methods that may beembodied in various forms. The exemplary embodiments are onlyillustrative and may, however, be embodied in many different forms andshould not be construed as limited to the exemplary embodiments setforth herein. Rather, these exemplary embodiments are provided so thatthis disclosure will be thorough and complete, and will fully convey thescope to be covered by the exemplary embodiments to those skilled in theart. In the description, details of well-known features and techniquesmay be omitted to avoid unnecessarily obscuring the presentedembodiments.

References in the specification to “one embodiment”, “an embodiment”,“an exemplary embodiment”, etc., indicate that the embodiment describedmay include a particular feature, structure, or characteristic, butevery embodiment may not necessarily include the particular feature,structure, or characteristic. Moreover, such phrases are not necessarilyreferring to the same embodiment. Further, when a particular feature,structure, or characteristic is described in connection with anembodiment, it is submitted that it is within the knowledge of oneskilled in the art to implement such feature, structure, orcharacteristic in connection with other embodiments whether or notexplicitly described.

In the interest of not obscuring the presentation of the exemplaryembodiments, in the following detailed description, some processingsteps or operations that are known in the art may have been combinedtogether for presentation and for illustration purposes and in someinstances may have not been described in detail. In other instances,some processing steps or operations that are known in the art may not bedescribed at all. It should be understood that the following descriptionis focused on the distinctive features or elements according to thevarious exemplary embodiments.

Humans often communicate with automated computers or machines, such asautomated phone call answering machines, smart speakers, smartassistants, and the like. In practice, it may be difficult for automatedcomputers or machines to adequately respond to humans or adequatelyfulfill their requests without understanding their intentions. In orderto understand human intentions, it is often necessary to understand theintents of human inputs and expression, such as a message, command,question, and the like. Moreover, often times such human expression mayinclude multiple intents, and such intents may be dependent on theresolving of other intents within the human inputs. It is thereforenecessary to resolve each of the intents of human expression toadequately understand and respond to human prompts.

Exemplary embodiments described herein provide a means for generating adependency graph resolution of a set of intent resolvers formulti-intent messages, featuring embedded questions, in which one ormore resolver inputs are not directly satisfied by a canonical text, butrather the output of one of the other resolvers. Dependency graphresolution comes into play when satisfying resolver inputs for multipleintents over a message is based on a specific order of execution for theintent resolvers.

Multi-intent messages with embedded questions are oftentimes associatedwith messaging/chat solutions in which questions can be formulated tobuild upon other questions. Thus, instead of having to pose multiplequestions to the system, a user can phrase questions such that portionsof the questions can be based on answers to other questions within thesame user expression. Such techniques improve existing AI systems byincreasing an efficiency at which it acquires the desired information.As used herein, an “intent resolver” can refer to any process or routinewith inputs and outputs that execute or process a particular intent orintents.

Accordingly, exemplary embodiments are directed to a method, computerprogram product, and computer system for resolving a multi-intentstatement having multiple embedded and dependent intents. Exemplaryembodiments may utilize entities and associated classes, inputs/outputs,and functions known as resolvers in order to resolve each of theembedded intents and overall user intent. Use cases of the exemplaryembodiments include automated call answering machines, smart devices,smart assistants, etc. In general, it will be appreciated thatembodiments described herein may relate to aiding in the resolver of theintents of user expression within any environment.

FIG. 1 depicts the intent resolver system 100, in accordance with theexemplary embodiments. According to the exemplary embodiments, theintent resolver system 100 may include a smart device 120 and an intentresolver server 130, which may be interconnected via a network 108.While programming and data of the exemplary embodiments may be storedand accessed remotely across several servers via the network 108,programming and data of the exemplary embodiments may alternatively oradditionally be stored locally on as few as one physical computingdevice or amongst other computing devices than those depicted.

In the exemplary embodiments, the network 108 may be a communicationchannel capable of transferring data between connected devices.Accordingly, the components of the intent resolver system 100 mayrepresent network components or network devices interconnected via thenetwork 108. In the exemplary embodiments, the network 108 may be theInternet, representing a worldwide collection of networks and gatewaysto support communications between devices connected to the Internet.Moreover, the network 108 may utilize various types of connections suchas wired, wireless, fiber optic, etc. which may be implemented as anintranet network, a local area network (LAN), a wide area network (WAN),or a combination thereof. In further embodiments, the network 108 may bea Bluetooth network, a Wi-Fi network, or a combination thereof. In yetfurther embodiments, the network 108 may be a telecommunications networkused to facilitate telephone calls between two or more partiescomprising a landline network, a wireless network, a closed network, asatellite network, or a combination thereof. In general, the network 108may represent any combination of connections and protocols that willsupport communications between connected devices.

In the example embodiment, the smart device 120 includes an intentresolver client 122, and may be an enterprise server, a laptop computer,a notebook, a tablet computer, a netbook computer, a personal computer(PC), a desktop computer, a server, a personal digital assistant (PDA),a rotary phone, a touchtone phone, a smart phone, a mobile phone, avirtual device, a thin client, an IoT device, or any other electronicdevice or computing system capable of receiving and sending data to andfrom other computing devices. While the smart device 120 is shown as asingle device, in other embodiments, the smart device 120 may becomprised of a cluster or plurality of computing devices, in a modularmanner, etc., working together or working independently. The smartdevice 120 is described in greater detail as a hardware implementationwith reference to FIG. 5, as part of a cloud implementation withreference to FIG. 6, and/or as utilizing functional abstraction layersfor processing with reference to FIG. 7.

The intent resolver client 122 may be a software and/or hardwareapplication capable of communicating with and providing a user interfacefor a user to interact with a server via the network 108. The intentresolver client 122 may act as a client in a client-server relationship.Moreover, in the example embodiment, the intent resolver client 122 maybe capable of transferring data between the smart device 120 and otherdevices via the network 108. In embodiments, the intent resolver 134utilizes various wired and wireless connection protocols for datatransmission and exchange, including Bluetooth, 2.4 gHz and 5 gHzinternet, near-field communication, Z-Wave, Zigbee, etc. The intentresolver client 122 is described in greater detail with respect to FIG.2.

In the exemplary embodiments, the intent resolver server 130 includesone or more intent databases 132 and an intent resolver 134. The intentresolver server 130 may act as a server in a client-server relationshipwith the intent resolver client 122, and may be an enterprise server, alaptop computer, a notebook, a tablet computer, a netbook computer, aPC, a desktop computer, a server, a PDA, a rotary phone, a touchtonephone, a smart phone, a mobile phone, a virtual device, a thin client,an IoT device, or any other electronic device or computing systemcapable of receiving and sending data to and from other computingdevices. While the intent resolver server 130 is shown as a singledevice, in other embodiments, the intent resolver server 130 may becomprised of a cluster or plurality of computing devices, workingtogether or working independently. The intent resolver server 130 isdescribed in greater detail as a hardware implementation with referenceto FIG. 5, as part of a cloud implementation with reference to FIG. 6,and/or as utilizing functional abstraction layers for processing withreference to FIG. 7.

In the exemplary embodiments, the intent databases 132 may be acollection of organized data which details information associating oneor more user expressions, entities, classifications, resolvers, resolverinput/output classes, and intents. As used herein, a user expression,such as an action, question, statement, etc., may include one or moreabstract or physical entities such as persons, organizations, locations,products, ideas, etc. For example, a user input inquiring “does aspirintreat a headache?” includes the entities aspirin and headache. Eachentity may be further associated with a class describing a category ofthe entity. For example, aspirin may be associated with the class“medication”, denoted aspirin [medication], and headache may beassociated with the class “symptom”, denoted headache [symptom].Moreover, the one or more entities and one or more classes may befurther associated with one or more functions known as resolvers. Inembodiments, the resolvers may resolve a query associated with anentity. For example, entities classified as a [medication] may beassociated with the resolver “medTreats” that functions to resolve whichcondition class entities the medication entity treats. The resolvers maybe further associated with natural language training sentencesassociated with the resolver function. For example, the resolver“medTreats” may be associated with the natural language trainingsentence “what [condition] does [medication] treat?” Lastly, resolversmay be associated with specific input classes and output classesdefining which kinds of information each resolver may receive as inputand generate as an output. Exemplary information stored within theintent databases 132 are illustrated by Table 1 illustrates, below. Insome embodiments, the intent databases 132 may additionally includevectors, graphs, or other visual representations of data, such asvectors to be analyzed with cosine similarity models or bar graphs to beanalyzed with bag of words models. In the example embodiment, the intentdatabases 132 is stored remotely on the intent resolver server 130. Inother embodiments, however, the intent databases 132 may be storedelsewhere, such as locally on the smart device 120. The intent databases132 are described in greater detail with respect to FIG. 2.

TABLE 1 Additional Example Resolvers Resolver Input Class Output ClassTraining Phrase getConditionSymptoms [condition] [symptoms] “What arethe [symptoms]of [condition]?” getConditionMeds [condition] [medication]“What [medications] are used to treat [condition]?” getMedSideEffects[medication] [side_effect] “What are the [side_effects] of[medication]?” getMedCost [medication] [cost] “How much does[medication] [cost]?” getMedForSideEffects [side_effect] [medication]“What [medications] are used to treat [side effect]?” getMedForCondition[condition] [medication] “What [medications] are used to treat[condition]?” getSideEffectOTCMeds [side_effect] [otc_meds] “What[otc_meds] are used to treat [side_effect]?”

The intent resolver 134 may be a software and/or hardware programcapable of receiving a user expression, receiving a first resolverhaving an input class and an output class based on the user expression,determining whether the first resolver can be resolved based on the userexpression, and based on determining that the first resolver can beresolved based on the user expression, resolving the first resolver. Theintent resolver 134 is described in greater detail with reference toFIG. 2.

FIG. 2 depicts an exemplary flowchart 200 illustrating the operations ofan intent resolver 134 of the intent resolver system 100 in resolvinguser intents, in accordance with the exemplary embodiments.

The intent resolver 134 may collect or receive data relating to userexpression (step 204). User expression may include natural language,body/gestural language, sign, language, facial expression, text, etc.,and may be communicated to the intent resolver 134 via the intentresolver client 122 in the form of audio, video, image, message, etc. Inembodiments, the user expression may comprise one or more words, one ormore sentences, one or more paragraphs, etc. When receiving userexpression in the form of text, the intent resolver 134 may receive andprocess the textual user expression using natural language processingand machine learning techniques. When receiving the user expression inthe form of spoken natural language, the intent resolver 134 mayextract, translate, transcribe, process, etc. the spoken naturallanguage before processing the user expression as text, as describedabove. When receiving user expression in the form of gestural language,sign language, facial expression, or other visual expression, the intentresolver 134 may implement image and video analysis techniques incombination with referential databases in order to extract userexpression. In further embodiments, additional means of user expressionand user expression extraction may be contemplated.

To further illustrate the operations of the intent resolver 134,reference is now made to FIG. 3-4 which depict an illustrative examplewhere the intent resolver 134 receives the user expression: “Which overthe counter medications help manage the side effects of COPDmedications?”

The intent resolver 134 may receive one or more classified intents overthe user expression and appropriate resolvers for each classified intent(step 206). The intent resolver 134 may receive one or more classifiedintents over the user expression and appropriate resolvers for eachclassified intent from an external resource such as a corpus or questionand answer service. The received one or more appropriate resolvers mayinclude input classes and output classes.

With reference to the previously introduced example illustrated by FIG.3-4, where the intent resolver 134 receives the user expression: “Whichover the counter medications help manage the side effects of COPDmedications?”, the intent resolver receives intents and their followingcorresponding resolvers from an external resource: getSideEffectOTCMeds,getMedSideEffects, and getConditionMeds.

The intent resolver 134 may extract and satisfy the first tier resolvers(step 208). The intent resolver 134 may extract the first tier resolverby determining which one of the received resolvers has an input that issatisfied by the received user expression. The intent resolver 134 maysatisfy the appropriate first tier resolver by answering the resolverand/or intent or determining the output of the resolver and/or intentvia reference to the user expression or an external resource such as acorpus or question and answer service. In some embodiments, the intentresolver 134 may check to make sure all the previously received intentresolvers can properly act upon the received user expression. In someembodiments, the intent resolver 134 may determine the dependency of thereceived resolvers based on their input and output classes before orwithout satisfying the resolvers.

With reference to the previously introduced example illustrated by FIG.3-4, where the intent resolver 134 receives resolversgetSideEffectOTCMeds, getMedSideEffects, and getConditionMeds, theintent resolver 134 determines that getConditionMeds is the onlyresolver whose input is satisfied directly by entities within the userexpression ([condition]=COPD) and extracts resolver getConditionMeds.The intent resolver 134 satisfies resolver getConditionMeds bydetermining the resolver's output: Ipratropium and Budesonide.

The intent resolver 134 may extract and satisfy an additional receivedresolver. The intent resolver 134 may identify the dependency of one ormore additional received resolvers by comparing the output of thepreviously identified first tier resolver with the inputs of the otherreceived resolvers. In the event that the output of the first tierresolver satisfies the input of an additional received resolver, theadditional received resolver is extracted and satisfied. In furtheriterations, the inputs of additional received resolvers are compared tothe output of the preceding satisfied resolver.

With reference to the previously introduced example illustrated by FIG.3-4, where the intent resolver 134 satisfies resolver getConditionMedsand determines the resolver's output: Ipratropium and Budesonide, theintent resolver 134 extracts resolver getMedSideEffects as having inputsatisfied ([medication]=Ipratropium and Budesonide) by the output ofgetConditionMeds. The intent resolver 134 satisfies resolvergetMedSideEffects with output: Bronchitis, Nausea, Fatigue, andHeadache.

The intent resolver 134 may determine whether there are furtheradditional received resolvers (decision 212). In the event that theintent resolver 134 determines that there are additional receivedresolvers (decision 212 “YES” branch), the intent resolver 134 mayidentify and satisfy one or more additional resolvers (step 210). Theintent resolver 134 may further iterate decision 212 until the intentresolver 134 determines that there are no further additional receivedresolvers. In the event that the intent resolver 134 determines thatthere are no additional received resolvers (decision 212 “NO” branch),the intent resolver 134 may cease to extract and satisfy resolvers. Inembodiments, upon determining that there are no additional resolvers,the intent resolver 134 may output, export, display, etc. the dependencyand/or order of the extracted intents and/or satisfied resolvers. Forexample, the intent resolver 134 may export the extracted resolvers inthe form of a collated list based on the dependency of a receivedresolver and/or intent on the output of another extracted resolverand/or intent. In embodiments, the intent resolver 134 may further storethe processed user expression and associated intents for futureprocessing.

With reference to the previously introduced example illustrated by FIG.3-4, where the intent resolver 134 satisfies resolver getMedSideEffectswith outputs: Bronchitis, Nausea, Fatigue, and Headache, the intentresolver 134 determines that the additional received resolvergetSideEffectOTCMeds has its input satisfied ([side_effect]=Bronchitis,Nausea, Fatigue and Headache) and extracts getSideEffectOTCMeds. Theintent resolver 134 satisfies resolver getSideEffectOTCMeds withoutputs: Aspirin, Acetaminophen, Ibuprofen, Kaopectate, Pepto-Bismol,Dramamine, Vivarin, NoDoz, and Naproxen. The intent resolver 134 exportsthe dependency of the resolvers and their outputs in the form of adependency graph as illustrated in FIG. 4.

FIG. 3 depicts an illustrative example of the intent resolver system 100resolving a user expression, in accordance with the exemplaryembodiments.

FIG. 4 depicts an illustrative example of a collated output based ondependency generated by the intent resolver system 100 in resolving theuser expression of FIG. 3, in accordance with the exemplary embodiments.

FIG. 5 depicts a block diagram of devices within the intent resolver 134of the intent resolver system 100 of FIG. 1, in accordance with theexemplary embodiments. It should be appreciated that FIG. 5 providesonly an illustration of one implementation and does not imply anylimitations with regard to the environments in which differentembodiments may be implemented. Many modifications to the depictedenvironment may be made.

Devices used herein may include one or more processors 02, one or morecomputer-readable RAMs 04, one or more computer-readable ROMs 06, one ormore computer readable storage media 08, device drivers 12, read/writedrive or interface 14, network adapter or interface 16, allinterconnected over a communications fabric 18. Communications fabric 18may be implemented with any architecture designed for passing dataand/or control information between processors (such as microprocessors,communications and network processors, etc.), system memory, peripheraldevices, and any other hardware components within a system.

One or more operating systems 10, and one or more application programs11 are stored on one or more of the computer readable storage media 08for execution by one or more of the processors 02 via one or more of therespective RAMs 04 (which typically include cache memory). In theillustrated embodiment, each of the computer readable storage media 08may be a magnetic disk storage device of an internal hard drive, CD-ROM,DVD, memory stick, magnetic tape, magnetic disk, optical disk, asemiconductor storage device such as RAM, ROM, EPROM, flash memory orany other computer-readable tangible storage device that can store acomputer program and digital information.

Devices used herein may also include a R/W drive or interface 14 to readfrom and write to one or more portable computer readable storage media26. Application programs 11 on said devices may be stored on one or moreof the portable computer readable storage media 26, read via therespective R/W drive or interface 14 and loaded into the respectivecomputer readable storage media 08.

Devices used herein may also include a network adapter or interface 16,such as a TCP/IP adapter card or wireless communication adapter (such asa 4G wireless communication adapter using OFDMA technology). Applicationprograms 11 on said computing devices may be downloaded to the computingdevice from an external computer or external storage device via anetwork (for example, the Internet, a local area network or other widearea network or wireless network) and network adapter or interface 16.From the network adapter or interface 16, the programs may be loadedonto computer readable storage media 08. The network may comprise copperwires, optical fibers, wireless transmission, routers, firewalls,switches, gateway computers and/or edge servers.

Devices used herein may also include a display screen 20, a keyboard orkeypad 22, and a computer mouse or touchpad 24. Device drivers 12interface to display screen 20 for imaging, to keyboard or keypad 22, tocomputer mouse or touchpad 24, and/or to display screen 20 for pressuresensing of alphanumeric character entry and user selections. The devicedrivers 12, R/W drive or interface 14 and network adapter or interface16 may comprise hardware and software (stored on computer readablestorage media 08 and/or ROM 06).

The programs described herein are resolved based upon the applicationfor which they are implemented in a specific one of the exemplaryembodiments. However, it should be appreciated that any particularprogram nomenclature herein is used merely for convenience, and thus theexemplary embodiments should not be limited to use solely in anyspecific application identified and/or implied by such nomenclature.

Based on the foregoing, a computer system, method, and computer programproduct have been disclosed. However, numerous modifications andsubstitutions can be made without deviating from the scope of theexemplary embodiments. Therefore, the exemplary embodiments have beendisclosed by way of example and not limitation.

It is to be understood that although this disclosure includes a detaileddescription on cloud computing, implementation of the teachings recitedherein are not limited to a cloud computing environment. Rather, theexemplary embodiments are capable of being implemented in conjunctionwith any other type of computing environment now known or laterdeveloped.

Cloud computing is a model of service delivery for enabling convenient,on-demand network access to a shared pool of configurable computingresources (e.g., networks, network bandwidth, servers, processing,memory, storage, applications, virtual machines, and services) that canbe rapidly provisioned and released with minimal management effort orinteraction with a provider of the service. This cloud model may includeat least five characteristics, at least three service models, and atleast four deployment models.

Characteristics are as follows:

On-demand self-service: a cloud consumer can unilaterally provisioncomputing capabilities, such as server time and network storage, asneeded automatically without requiring human interaction with theservice's provider.

Broad network access: capabilities are available over a network andaccessed through standard mechanisms that promote use by heterogeneousthin or thick client platforms (e.g., mobile phones, laptops, and PDAs).

Resource pooling: the provider's computing resources are pooled to servemultiple consumers using a multi-tenant model, with different physicaland virtual resources dynamically assigned and reassigned according todemand. There is a sense of location independence in that the consumergenerally has no control or knowledge over the exact location of theprovided resources but may be able to specify location at a higher levelof abstraction (e.g., country, state, or data center).

Rapid elasticity: capabilities can be rapidly and elasticallyprovisioned, in some cases automatically, to quickly scale out andrapidly released to quickly scale in. To the consumer, the capabilitiesavailable for provisioning often appear to be unlimited and can bepurchased in any quantity at any time.

Measured service: cloud systems automatically control and optimizeresource use by leveraging a metering capability at some level ofabstraction appropriate to the type of service (e.g., storage,processing, bandwidth, and active user accounts). Resource usage can bemonitored, controlled, and reported, providing transparency for both theprovider and consumer of the utilized service.

Service Models are as follows:

Software as a Service (SaaS): the capability provided to the consumer isto use the provider's applications running on a cloud infrastructure.The applications are accessible from various client devices through athin client interface such as a web browser (e.g., web-based e-mail).The consumer does not manage or control the underlying cloudinfrastructure including network, servers, operating systems, storage,or even individual application capabilities, with the possible exceptionof limited user-specific application configuration settings.

Platform as a Service (PaaS): the capability provided to the consumer isto deploy onto the cloud infrastructure consumer-created or acquiredapplications created using programming languages and tools supported bythe provider. The consumer does not manage or control the underlyingcloud infrastructure including networks, servers, operating systems, orstorage, but has control over the deployed applications and possiblyapplication hosting environment configurations.

Infrastructure as a Service (IaaS): the capability provided to theconsumer is to provision processing, storage, networks, and otherfundamental computing resources where the consumer is able to deploy andrun arbitrary software, which can include operating systems andapplications. The consumer does not manage or control the underlyingcloud infrastructure but has control over operating systems, storage,deployed applications, and possibly limited control of select networkingcomponents (e.g., host firewalls).

Deployment Models are as follows:

Private cloud: the cloud infrastructure is operated solely for anorganization. It may be managed by the organization or a third party andmay exist on-premises or off-premises.

Community cloud: the cloud infrastructure is shared by severalorganizations and supports a specific community that has shared concerns(e.g., mission, security requirements, policy, and complianceconsiderations). It may be managed by the organizations or a third partyand may exist on-premises or off-premises.

Public cloud: the cloud infrastructure is made available to the generalpublic or a large industry group and is owned by an organization sellingcloud services.

Hybrid cloud: the cloud infrastructure is a composition of two or moreclouds (private, community, or public) that remain unique entities butare bound together by standardized or proprietary technology thatenables data and application portability (e.g., cloud bursting forload-balancing between clouds).

A cloud computing environment is service oriented with a focus onstatelessness, low coupling, modularity, and semantic interoperability.At the heart of cloud computing is an infrastructure that includes anetwork of interconnected nodes.

Referring now to FIG. 6, illustrative cloud computing environment 50 isdepicted. As shown, cloud computing environment 50 includes one or morecloud computing nodes 40 with which local computing devices used bycloud consumers, such as, for example, personal digital assistant (PDA)or cellular telephone 54A, desktop computer 54B, laptop computer 54C,and/or automobile computer system 54N may communicate. Nodes 40 maycommunicate with one another. They may be grouped (not shown) physicallyor virtually, in one or more networks, such as Private, Community,Public, or Hybrid clouds as described hereinabove, or a combinationthereof. This allows cloud computing environment 50 to offerinfrastructure, platforms and/or software as services for which a cloudconsumer does not need to maintain resources on a local computingdevice. It is understood that the types of computing devices 54A-N shownin FIG. 6 are intended to be illustrative only and that computing nodes40 and cloud computing environment 50 can communicate with any type ofcomputerized device over any type of network and/or network addressableconnection (e.g., using a web browser).

Referring now to FIG. 7, a set of functional abstraction layers providedby cloud computing environment 50 (FIG. 6) is shown. It should beunderstood in advance that the components, layers, and functions shownin FIG. 7 are intended to be illustrative only and the exemplaryembodiments are not limited thereto. As depicted, the following layersand corresponding functions are provided:

Hardware and software layer 60 includes hardware and softwarecomponents. Examples of hardware components include: mainframes 61; RISC(Reduced Instruction Set Computer) architecture based servers 62;servers 63; blade servers 64; storage devices 65; and networks andnetworking components 66. In some embodiments, software componentsinclude network application server software 67 and database software 68.

Virtualization layer 70 provides an abstraction layer from which thefollowing examples of virtual entities may be provided: virtual servers71; virtual storage 72; virtual networks 73, including virtual privatenetworks; virtual applications and operating systems 74; and virtualclients 75.

In one example, management layer 80 may provide the functions describedbelow. Resource provisioning 81 provides dynamic procurement ofcomputing resources and other resources that are utilized to performtasks within the cloud computing environment. Metering and Pricing 82provide cost tracking as resources are utilized within the cloudcomputing environment, and billing or invoicing for consumption of theseresources. In one example, these resources may include applicationsoftware licenses. Security provides identity verification for cloudconsumers and tasks, as well as protection for data and other resources.User portal 83 provides access to the cloud computing environment forconsumers and system administrators. Service level management 84provides cloud computing resource allocation and management such thatrequired service levels are met. Service Level Agreement (SLA) planningand fulfillment 85 provide pre-arrangement for, and procurement of,cloud computing resources for which a future requirement is anticipatedin accordance with an SLA.

Workloads layer 90 provides examples of functionality for which thecloud computing environment may be utilized. Examples of workloads andfunctions which may be provided from this layer include: mapping andnavigation 91; software development and lifecycle management 92; virtualclassroom education delivery 93; data analytics processing 94;transaction processing 95; and intent resolver 96.

The present invention may be a system, a method, and/or a computerprogram product at any possible technical detail level of integration.The computer program product may include a computer readable storagemedium (or media) having computer readable program instructions thereonfor causing a processor to carry out aspects of the present invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, configuration data for integrated circuitry, oreither source code or object code written in any combination of one ormore programming languages, including an object oriented programminglanguage such as Smalltalk, C++, or the like, and procedural programminglanguages, such as the “C” programming language or similar programminglanguages. The computer readable program instructions may executeentirely on the user's computer, partly on the user's computer, as astand-alone software package, partly on the user's computer and partlyon a remote computer or entirely on the remote computer or server. Inthe latter scenario, the remote computer may be connected to the user'scomputer through any type of network, including a local area network(LAN) or a wide area network (WAN), or the connection may be made to anexternal computer (for example, through the Internet using an InternetService Provider). In some embodiments, electronic circuitry including,for example, programmable logic circuitry, field-programmable gatearrays (FPGA), or programmable logic arrays (PLA) may execute thecomputer readable program instructions by utilizing state information ofthe computer readable program instructions to personalize the electroniccircuitry, in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a computer, or other programmable data processing apparatusto produce a machine, such that the instructions, which execute via theprocessor of the computer or other programmable data processingapparatus, create means for implementing the functions/acts specified inthe flowchart and/or block diagram block or blocks. These computerreadable program instructions may also be stored in a computer readablestorage medium that can direct a computer, a programmable dataprocessing apparatus, and/or other devices to function in a particularmanner, such that the computer readable storage medium havinginstructions stored therein comprises an article of manufactureincluding instructions which implement aspects of the function/actspecified in the flowchart and/or block diagram block or blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the blocks may occur out of theorder noted in the Figures. For example, two blocks shown in successionmay, in fact, be accomplished as one step, executed concurrently,substantially concurrently, in a partially or wholly temporallyoverlapping manner, or the blocks may sometimes be executed in thereverse order, depending upon the functionality involved. It will alsobe noted that each block of the block diagrams and/or flowchartillustration, and combinations of blocks in the block diagrams and/orflowchart illustration, can be implemented by special purposehardware-based systems that perform the specified functions or acts orcarry out combinations of special purpose hardware and computerinstructions.

What is claimed is:
 1. A computer-implemented method for resolvingresolvers, the method comprising: receiving a user expression; receivinga first resolver having an input class and an output class based on theuser expression; determining whether the first resolver can be resolvedbased on the user expression; and based on determining that the firstresolver can be resolved based on the user expression, resolving thefirst resolver.
 2. The method of claim 1, wherein determining whetherthe first resolver can be resolved based on the user expression furthercomprises: determining whether the input class associated with the firstresolver is included within the user expression.
 3. The method of claim1, further comprising: based on determining that the first resolvercannot be resolved based on the user expression, determining whether asecond resolver can be resolved based on the user expression.
 4. Themethod of claim 3, further comprising: based on determining that thesecond resolver can be resolved based on the user expression, resolvingthe second resolver to generate a second output based on the userexpression.
 5. The method of claim 4, further comprising: determiningwhether the second output can resolve the first resolver based on theinput class associated with the first resolver; and based on determiningthat the second output can resolve the first resolver based on the inputclass associated with the first resolver, resolving the first resolverbased on the second output.
 6. The method of claim 1, wherein the firstresolver and the second resolver each correspond to a user intent. 7.The method of claim 1, further comprising displaying at least one of thefirst resolver, the first output, the second resolver, and the secondoutput in at least the form of a list or resolver dependency graph.
 8. Acomputer program product for resolving resolvers, the computer programproduct comprising: one or more non-transitory computer-readable storagemedia and program instructions stored on the one or more non-transitorycomputer-readable storage media capable of performing a method, themethod comprising: receiving a user expression; receiving a firstresolver having an input class and an output class based on the userexpression; determining whether the first resolver can be resolved basedon the user expression; and based on determining that the first resolvercan be resolved based on the user expression, resolving the firstresolver.
 9. The computer program product of claim 8, whereindetermining whether the first resolver can be resolved based on the userexpression further comprises: determining whether the input classassociated with the first resolver is included within the userexpression.
 10. The computer program product of claim 8, furthercomprising: based on determining that the first resolver cannot beresolved based on the user expression, determining whether a secondresolver can be resolved based on the user expression.
 11. The computerprogram product of claim 10, further comprising: based on determiningthat the second resolver can be resolved based on the user expression,resolving the second resolver to generate a second output based on theuser expression.
 12. The computer program product of claim 11, furthercomprising: determining whether the second output can resolve the firstresolver based on the input class associated with the first resolver;and based on determining that the second output can resolve the firstresolver based on the input class associated with the first resolver,resolving the first resolver based on the second output.
 13. Thecomputer program product of claim 8, wherein the first resolver and thesecond resolver each correspond to a user intent.
 14. The computerprogram product of claim 8, further comprising displaying at least oneof the first resolver, the first output, the second resolver, and thesecond output in at least the form of a list or resolver dependencygraph.
 15. A computer system for resolving resolvers, the computersystem comprising: one or more computer processors, one or morecomputer-readable storage media, and program instructions stored on theone or more of the computer-readable storage media for execution by atleast one of the one or more processors capable of performing a method,the method comprising: receiving a user expression; receiving a firstresolver having an input class and an output class based on the userexpression; determining whether the first resolver can be resolved basedon the user expression; and based on determining that the first resolvercan be resolved based on the user expression, resolving the firstresolver.
 16. The computer system of claim 15, wherein determiningwhether the first resolver can be resolved based on the user expressionfurther comprises: determining whether the input class associated withthe first resolver is included within the user expression.
 17. Thecomputer system of claim 15, further comprising: based on determiningthat the first resolver cannot be resolved based on the user expression,determining whether a second resolver can be resolved based on the userexpression.
 18. The computer system of claim 17, further comprising:based on determining that the second resolver can be resolved based onthe user expression, resolving the second resolver to generate a secondoutput based on the user expression.
 19. The computer system of claim18, further comprising: determining whether the second output canresolve the first resolver based on the input class associated with thefirst resolver; and based on determining that the second output canresolve the first resolver based on the input class associated with thefirst resolver, resolving the first resolver based on the second output.20. The computer system of claim 15, wherein the first resolver and thesecond resolver each correspond to a user intent.